Lune

ACL2024顶会

TaPERA: Enhancing Faithfulness and Interpretability in Long-Form Table QA by Content Planning and Execution-based Reasoning

Yilun Zhao, Lyuhao Chen, Arman Cohan, Chen Zhao

2024年份
5被引次数
11顶会引用

摘要

Long-form Table Question Answering (LFTQA) requires systems to generate paragraph long and complex answers to questions over tabular data. While Large language models based systems have made significant progress, it often hallucinates, especially when the task involves complex reasoning over tables. To tackle this issue, we propose a new LLM-based framework, TAPERA, for LFTQA tasks. Our framework uses a modular approach that decomposes the whole process into three sub-modules: 1) QA-based Content Planner that iteratively decomposes the input question into sub-questions; 2) Execution-based Table Reasoner that produces executable Python program for each sub-question; and 3) Answer Generator that generates long-form answer grounded on the program output. Human evaluation results on the FETAQA and QTSUMM datasets indicate that our framework significantly improves strong baselines on both accuracy and truthfulness, as our modular framework is better at table reasoning, and the long-form answer is always consistent with the program output. Our modular design further provides transparency as users are able to interact with our framework by manually changing the content plans. https://github.com/yilunzhao/TaPERA Plan-based Answer Generation Direct Answer Generation Q1: Which company earns the highest profit in the Oil and Gas industry? A1: Sinopec Group earns the highest profit in the Oil and Gas industry. Q2: Which company earns the overall highest profit? A2: Apple earns the overall highest profit. Q3: Compare these two companies. A3: [pending] Q1: Which company earns the highest profit in the Oil and Gas industry? A1: Sinopec Group earns the highest profit in the Oil and Gas industry. Q2: Which company earns the overall highest profit? A2: Apple earns the overall highest profit. Q3: Compare these two companies. A3: Apple is in the electronics industry, while Sinopec Group is in the Oil and Gas industry.

问问这篇 Paper

智能体会读完全文。

Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。

可以从这些问题问起

智能体调用

Luneget_paper_fulltext

在 Lune 里问

免费开始,无需绑卡

引用它的顶会 Paper11

问问它们各自怎么用它

它引用的顶会 Paper25

相关 Paper

黄昏的海面,两侧是细线勾勒的悬崖